Analysis of Overall E-Business Solution on Personalized Medical Care ——Taking Private Hospitals for Example

The patient is the lifeblood of the hospital and only win customers can win the future. When choosing a hospital, in addition to the strength of the medical treatment of the hospital itself, patients considering most are the services of the hospital which is the very factor that can influence customer making decision. Clearly, the needs of patients can’t be achieved in overcrowded public hospitals. This paper starts from the content of E-Business, analyzes the current situation and problems of private hospital development, points out that development of E-Business to enhance customer relationship management is the only way to solve the practical problems of private hospitals, gives personal attention of private hospitals overall E-Business solutions and development strategies

The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)

Automated brain tumor segmentation methods have become well-established and reached performance levels offering clear clinical utility. These methods typically rely on four input magnetic resonance imaging (MRI) modalities: T1-weighted images with and without contrast enhancement, T2-weighted images, and FLAIR images. However, some sequences are often missing in clinical practice due to time constraints or image artifacts, such as patient motion. Consequently, the ability to substitute missing modalities and gain segmentation performance is highly desirable and necessary for the broader adoption of these algorithms in the clinical routine. In this work, we present the establishment of the Brain MR Image Synthesis Benchmark (BraSyn) in conjunction with the Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2023. The primary objective of this challenge is to evaluate image synthesis methods that can realistically generate missing MRI modalities when multiple available images are provided. The ultimate aim is to facilitate automated brain tumor segmentation pipelines. The image dataset used in the benchmark is diverse and multi-modal, created through collaboration with various hospitals and research institutions.Comment: Technical report of BraSy

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Validation of the Information-Technology-Enabled Interaction Instrument in Contemporary Chinese Context

Practitioners and researchers have shown great interest in information-technology (IT)-enabled interactions across partnering firms and developed instruments for measuring it. However, those instruments might have been under criticism as they were developed before the widespread adoption of the new IT applications like video conferences, DingTalk and WeChat Moments among Chinese managers for the last five years. The purpose of this study is to validate the instrument of IT-enabled formal and informal interactions for the contemporary Chinese context. First, the study reviews the literature on IT-enabled interfirm interactions and designs an open questionnaire through in-depth interviews. Answers from 85 pairs of suppliers and manufacturers are coded and the preliminary item pool is generated through the qualitative analysis. Next, a small-scale pretest with 120 manufacturing firms is conducted to purify and modify the item pool. Finally, a large-scale analysis with 336 manufacturing firms is conducted to check the reliability and validity of the measurements. The finalized scale yields six items measuring IT-enabled formal interaction and five items measuring IT-enabled informal interaction, among which six are newly derived in this study. The validated instrument reveals satisfactory reliability and validity and can serve as the basic instruments for future research on IT-enabled interactions

Results of industry linkage effects.

This paper theoretically analyzes and empirically examines the impact and mechanisms of automated machines on employment in manufacturing enterprises, drawing on task-based model and using micro data from listed Chinese manufacturing enterprises between 2012 and 2019. Our findings reveal that: (1) Automated machines in manufacturing enterprises leads to a substitution effect on the total labor force, with a substitution effect on low-skilled labor and a creation effect on high-skilled labor in terms of employment structure. (2) Further analysis indicates that automated machines primarily have a positive effect on R&D and technical staff, a non-significant effect on sales staff, and a negative impact on production, administrative, and financial staff. (3) The primary influencing mechanisms of automated machines on employment in manufacturing firms are productivity effects and output scale effects, based on the mediation effect model. (4) Considering the industry linkage effect, we employ the input-output method and the Input-Output Table and find that automated machines for upstream (downstream) manufacturing enterprises will result in a substitution effect on employment for downstream (upstream) enterprises. The novelties and research contributions are as follows: (1) we conduct a structural decomposition of total employment, and further decompose employment positions into production, R&D, sales, finance, and administration. (2) We try to investigate the industry linkage effect about the impact of automated machines on the employment of upstream and downstream enterprises. (3) We use data from listed manufacturing companies, and the data of existing research are about provincial and industry-level data.</div

Development of a Transposon Mutagenesis System in the Oral Spirochete Treponema denticola▿

Here, we report successful transposon mutagenesis in the oral spirochete Treponema denticola. A modified Himar1 transposon, including a new antibiotic selection cassette for T. denticola, generated mutations affecting cell division, transport, and chemotaxis, among other processes. This random mutagenesis system should facilitate research on the biology and pathogenesis of this spirochete, which is associated with human periodontal diseases

Intelligent Identification of Cavitation State of Centrifugal Pump Based on Support Vector Machine

In order to perform intelligent identification of the various stages of cavitation development, a micro high-speed centrifugal pump was used as a research object for vibration signal analysis and feature extraction for normal, incipient cavitation, cavitation and severely cavitated operating states of the pump at different temperatures (25 °C, 50 °C and 70 °C), based on support vector machines to classify and identify the eigenvalues in different cavitation states. The results of the study showed that the highest recognition rate of the individual eigenvalues of the time domain signals, followed by time frequency domain signals and finally frequency domain signals, was achieved in the binary classification of whether cavitation occurred or not. In the multi-classification recognition of the cavitation state, the eigenvalues of the time domain signals of the four monitoring points, the time frequency domain signals of the monitoring points in the X-direction of the inlet pipe and the Y-direction of the inlet pipe are combined, and the combined eigenvalues can achieve a multi-classification recognition rate of more than 94% for the cavitation state at different temperatures, which is highly accurate for the recognition of the cavitation state of centrifugal pumps